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An Examination of the Prior Use of E-Learning Within an Extended Technology Acceptance Model and the Factors That Influence the Behavioral Intention of Users to Use M-Learning

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  • Jonathan Abramson
  • Maurice Dawson
  • Jeffery Stevens

Abstract

The purpose of this empirical study was to test specific factors of behavioral intention to use m-learning in a community college setting using a modified technology acceptance model and antecedent factors suggested by the researcher’s review of the literature. In addition, the study’s purpose was to expand understanding of behavioral intention to use m-learning and to contribute to the growing body of research. This research model was based on relevant technology acceptance literature. The study examines the significance of “prior use of e-learning†and correlation with the behavioral intention to use m-learning. Existing models have looked at prior use of e-learning in other domains, but not specifically m-learning. Other models and studies have primarily looked at the prior use of e-learning variable as a moderating variable and not one that is directly related to attitude and behavioral intention. The study found that there is a relationship between prior use of e-learning and behavioral intention to use m-learning. This research direction was proposed by Lu and Viehland.

Suggested Citation

  • Jonathan Abramson & Maurice Dawson & Jeffery Stevens, 2015. "An Examination of the Prior Use of E-Learning Within an Extended Technology Acceptance Model and the Factors That Influence the Behavioral Intention of Users to Use M-Learning," SAGE Open, , vol. 5(4), pages 21582440156, December.
  • Handle: RePEc:sae:sagope:v:5:y:2015:i:4:p:2158244015621114
    DOI: 10.1177/2158244015621114
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    References listed on IDEAS

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    1. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    2. Said Al-Gahtani, 2001. "The Applicability of TAM Outside North America: An Empirical Test in the United Kingdom," Information Resources Management Journal (IRMJ), IGI Global, vol. 14(3), pages 37-46, July.
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    Cited by:

    1. Melih Engin & Nihat Kasap & Berna Tektas Sivrikaya, 2020. "User Acceptance of Shuttle Bus Decision Support System Based on Smartphone Probes," SAGE Open, , vol. 10(2), pages 21582440209, May.
    2. Quadri Noorulhasan Naveed & Mohammad Mahtab Alam & Nasser Tairan, 2020. "Structural Equation Modeling for Mobile Learning Acceptance by University Students: An Empirical Study," Sustainability, MDPI, vol. 12(20), pages 1-17, October.
    3. Nafiz A.Ali Ahmad & Abdelrahim M. Zabadi, 2022. "Using the Technology Acceptance Model (TAM) in Understanding the Preschool Teachers in Palestine Technology' Acceptance during the COVID-19 pandemic," Eximia Journal, Plus Communication Consulting SRL, vol. 4(1), pages 63-83, April.
    4. Abide Coskun-Setirek & Zuhal Tanrikulu, 2021. "M-Universities: Critical Sustainability Factors," SAGE Open, , vol. 11(1), pages 21582440219, March.

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